MARCADORES ELECTROENCEFALOGRÁFICOS Y FENOTIPO COGNITIVO EN LA ENFERMEDAD DE PARKINSON. UNA REVISIÓN SISTEMÁTICA
Palabras clave:
Biomarcadores, congnición, electroencefalografía, Revisión sistemática, Enfermedad de Parkinson, ElectrofisiologíaResumen
Contexto: La Enfermedad de Parkinson (EP) se caracteriza por un conjunto heterogéneo de síntomas no motores que afectan la calidad de vida de pacientes y cuidadores. El deterioro cognitivo se presenta desde etapas tempranas y constituye un factor de riesgo de demencia. Múltiples estudios electroencefalográficos (EEG) apuntan a cambios específicos en la actividad cerebral relacionados con la progresión y el fenotipo cognitivo de la enfermedad. Sin embargo, no está claro qué medidas electrofisiológicas son más útiles como marcadores biológicos. Objetivo: Sintetizar la evidencia científica que determina las relaciones entre el EEG en reposo y el perfil cognitivo en la EP. Métodos: Se desarrolló una revisión sistemática mediante una búsqueda en las bases de datos MEDLINE y Embase. Se incluyeron estudios en humanos con EP, en los que se especificase el estatus cognitivo, y se hubiese efectuado el análisis cuantitativo del EEG (qEEG) en reposo. Resultados: Se seleccionaron 36 artículos originales, encontrando tres grupos de medidas: análisis espectrales, conectividad funcional (CF), y métodos no-lineales. Todas las medidas diferenciaron los pacientes de los controles sanos (CS), indicando una relación directa con características fisiopatológicas y clínicas de la EP. Las medidas de análisis espectral mostraron correlaciones con el perfil neuropsicológico y/o capacidad predictiva para el pronóstico cognitivo de la enfermedad. Las medidas de conectividad demostraron sensibilidad a diversas intervenciones terapéuticas, aunque se encontró evidencia escasa acerca de su relación con variables cognitivas. Conclusiones: Las medidas obtenidas del qEEG en reposo configuran instrumentos costo-efectivos útiles como potenciales biomarcadores de la EP y sus manifestaciones cognitivas.
Biografía del autor/a
Jairo Alexander Carmona Arroyave, Universidad de Antioquia
MD, Cirujano, Maestría en Neurociencias. Grupo de Neurociencias de Antioquia, Grupo de Neuropsicología y Conducta, Facultad de Medicina, Universidad de Antioquia. Medellín, Colombia.
Carlos Andrés Tobón Quintero, Universidad de Antioquia
MD, Cirujano, PhD en Neurociencias. Grupo de Neurociencias de Antioquia, Grupo de Neuropsicología y Conducta, Facultad de Medicina, Universidad de Antioquia. Medellín, Colombia.
David Antonio Pineda Salazar, Universidad de Antioquia
MD, Cirujano, PhD Honoris causa en Neurociencias Cognitivas. Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia. Grupo de Neuropsicología y Conducta, Facultad de Psicología, Universidad de San Buenaventura. Medellín, Colombia.
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3. Obeso JA, Rodriguez-Oroz MC, Stamelou M, Bhatia KP, Burn DJ. The expanding universe of disorders of the basal ganglia. Lancet. 2014; 384(9942): 523–31.
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5. Jankovic J. Parkinson’s disease: clinical features and diagnosis. J Neurol Neurosurg Psychiatry. 2008; 79(4): 368–76.
6. Martinez-Martin P, Rodriguez-Blazquez C, Kurtis MM, Chaudhuri KR. The impact of non-motor symptoms on health-related quality of life of patients with Parkinson’s disease. Mov Disord. 2011; 26(3): 399–406.
7. Grun D, Pieri V, Vaillant M, Diederich NJ. Contributory Factors to Caregiver Burden in Parkinson Disease. J Am Med Dir Assoc. 2016; 17(7): 626–32.
8. Vossius C, Larsen JP, Janvin C, Aarsland D. The economic impact of cognitive impairment in Parkinson’s disease. Mov Disord. 2011; 26(8): 1541–4.
9. Aarsland D, Creese B, Politis M, Chaudhuri KR, Ffytche DH, Weintraub D, et al. Cognitive decline in Parkinson disease. Nat Rev Neurol. 2017; 13(4): 217–31.
10. Muslimovic D, Post B, Speelman JD, Schmand B. Cognitive profile of patients with newly diagnosed Parkinson disease. Neurology. 2005; 65(8): 1239–45.
11. Domellof ME, Ekman U, Forsgren L, Elgh E. Cognitive function in the early phase of Parkinson’s disease, a fiveyear follow-up. Acta Neurol Scand. 2015; 132(2): 79–88.
12. Hely MA, Reid WGJ, Adena MA, Halliday GM, Morris JGL. The Sydney multicenter study of Parkinson’s disease: the inevitability of dementia at 20 years. Mov Disord. 2008; 23(6): 837–44.
13. Algarni MA, Stoessl AJ. The role of biomarkers and imaging in Parkinson’s disease. Expert Rev Neurother. 2016; 16(2): 187–203.
14. Sporns O, Tononi G, Edelman GM. Connectivity and complexity: the relationship between neuroanatomy and brain dynamics. Neural Netw. 2000; 13(8–9): 909–22.
15. Bassett DS, Sporns O. Network neuroscience. Nat Neurosci. 2017; 20(3): 353–64.
16. Bressler SL, Menon V. Large-scale brain networks in cognition: emerging methods and principles. Trends Cogn Sci. 2010; 14(6): 277–90.
17. Lopes da Silva F. EEG and MEG: Relevance to Neuroscience. Neuron. 2017; 80(5): 1112–28.
18. Raichle ME. The restless brain: how intrinsic activity organizes brain function. Philos Trans R Soc Lond B Biol Sci. 2015; 370(1668).
19. Kanda PA de M, Anghinah R, Smidth MT, Silva JM. The clinical use of quantitative EEG in cognitive disorders. Dement Neuropsychol; 2009; 3: 195–203.
20. Higgins J, Green S, (editors). Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. Cochrane Collab. 2011.
21. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, Ioannidis JPA, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol. 2009; 62(10): e1-34.
22. Reeves B, Deeks J, Higgins J, Wells G. Chapter 13: Including non-randomized studies. In: Higgins JPT, Green S (editors), Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. Cochrane Collab. 2011.
23. Downs SH, Black N. The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions. J Epidemiol Community Health. 1998; 52(6): 377–84.
24. Lopez de Argumedo M, Reviriego E, Rico R, Sobradillo N, Hurtado de Saracho I. Revisión externa y validación de instrumentos metodológicos para la Lectura Crítica y la síntesis de la evidencia científica. Madrid Serv Evaluación Tecnol Sanit del País Vasco. 2006; Report No.2.
25. Soikkeli R, Partanen J, Soininen H, Pääkkönen A, Riekkinen P. Slowing of EEG in Parkinson’s disease. Electroencephalogr Clin Neurophysiol. 1991; 79(3): 159–65.
26. Garcia-Mas A, Rosinol-Far A, Roca-Bennasar M, Llinas J, Rossello-Mir J. Frontal lobe involvement and cortical and subcortical deterioration in Parkinson’s disease evaluated using quantified electroencephalography. Arch Neurobiol (Madr). 1991; 54(6): 303–10.
27. Pin JC, Neau JP, Paquereau J, Rostykus C, Guehl D, Aubert I, et al. [Comparative study by computerized EEG of dementia of the ALzheimer type and Parkinson’s disease with dementia]. NeurophysiolClin. 1992; 22(0987–7053): 301–12.
28. Primavera A, Novello P. Quantitative electroencephalography in Parkinson’s disease, dementia, depression and normal aging. Neuropsychobiology. 1992; 25(2): 102–5.
29. Stanzione P, Marciani MG, Maschio M, Bassetti MA, Spanedda F, Pierantozzi M, et al. Quantitative EEG changes in non-demented Parkinson’s disease patients before and during L-dopa therapy. Eur J Neurol. 1996; 3(4): 354–62.
30. Bonanni L, Thomas A, Tiraboschi P, Perfetti B, Varanese S, Onofrj M, et al. EEG comparisons in early Alzheimer’s disease, dementia with Lewy bodies and Parkinson’s disease with dementia patients with a 2-year follow-up. Brain. 2008 Mar; 131(3): 690–705.
31. Pugnetti L, Baglio F, Farina E, Alberoni M, Calabrese E, Gambini A, et al. EEG evidence of posterior cortical disconnection in PD and related dementias. Int J Neurosci. 2010; 120(2): 88–98.
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Cómo citar
[1]
Carmona Arroyave, J.A. et al. 2018. MARCADORES ELECTROENCEFALOGRÁFICOS Y FENOTIPO COGNITIVO EN LA ENFERMEDAD DE PARKINSON. UNA REVISIÓN SISTEMÁTICA. Medicina. 40, 3 (oct. 2018), 332–348.
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